RESEARCH PAPER
An Automatic UI Interaction Script Generator for Android Applications Using Activity Call Graph Analysis
Yining Liu 1
,  
Shih-Chi Wang 2
,  
Yang Yang 3
,  
Hung-Min Sun 2  
 
 
More details
Hide details
1
Guilin University of Electronic Technology, Guilin, Guangxi, CHINA
2
National Tsing Hua University, Hsinchu, TAIWAN
3
Fuzhou University, Fuzhou, CHINA
4
University of California Davis, Davis, California, USA
Online publish date: 2018-05-14
Publish date: 2018-05-14
 
EURASIA J. Math., Sci Tech. Ed 2018;14(7):3159–3179
KEYWORDS
ABSTRACT
As the Android’s growth in global market share, the security problem of Android OS becomes more and more serious. According to statistics, there are 84% of smartphone users use Android OS. The popularity brings not only wealth into Android market but also more and more malicious applications. Malicious developers want to steal private information such as credit card number, contacts, or email from Android phones. Android has sustained security issue for a long time. Academics also have put many efforts to solve the problem. Dynamic analysis is one of the methodologies for Android malware detection. Current execution of dynamic analysis needs to deploy heavy human resources. There is always someone needed to access the user interface manually, or the work can hardly be finished. In this work, we propose an approach on Android UI automation. Our implemented system output an Android monkeyrunner scripts, which is custom made for input Apk. The script program can trigger UI event automatically and deal with exception conditions while executed in monkeyrunner.
 
REFERENCES (16)
1.
Androguard. (n.d.). Retrieved from https://code.google.com/p/andr....
 
2.
Android – Wikipedia. (n.d.). Retrieved from https://en.wikipedia.org/wiki/... (operating system).
 
3.
Android monkey. (n.d.). Retrieved from https://developer.android.com/....
 
4.
Android monkeyrunner. (n.d.). Retrieved from https://developer.android.com/....
 
5.
Apktool. (2017). A tool for reverse engineering Android apk files. Retrieved from https://ibotpeaches.github.io/....
 
6.
Baskaran, B., & Ralescu, A. (2016). A Study of Android Malware Detection Techniques and Machine Learning. In Master of Arts in Intercultural Studies (MAICS), pp. 15-23.
 
7.
Faruki, P., Bharmal, A., Laxmi, V., Ganmoor, V., Gaur, M. S., Conti, M., & Rajarajan, M. (2014). Android security: A survey of issues, malware penetration and defences. Communications Surveys & Tutorials, IEEE, 17(2), 998 – 1022. https://doi.org/10.1109/COMST.....
 
8.
Genymotion emulators. (n.d.). Retrieved from https://www.genymotion.com.
 
9.
Google Play: number of available apps 2009-2017. (2017). Retrieved from https://www.statista.com/stati....
 
10.
Hou, O. (2012). A look at google bouncer. Retrieved from http://blog.trendmicro.com/tre....
 
11.
Hu, W., Tao, J., Ma, X., Zhou, W., Zhao, S., & Han, T. (2014). Migdroid: Detecting app-repackaging android malware via method invocation graph. In 23rd International Conference on Computer Communication and Networks (ICCCN), pp. 1–7. https://doi.org/10.1109/ICCCN.....
 
12.
Smartphone OS market share. (2017). IDC, Q1. Retrieved from https://www.idc.com/promo/smar....
 
13.
Smieh. (2012). Anatomy physiology of an android. Retrieved from https://commons.wikimedia.org/....
 
14.
Zhang, L., Niu, Y., Wu, X., Wang, Z., & Xue, Y. (2013). Automatic analysis of android malware. In International Workshop on Cloud Computing and Information Security (CCIS), pp. 89-93.
 
15.
Zheng, C., Zhu, S., Dai, S., Gu, G., Gong, X., Han, X., & Zou, W. (2012). Smartdroid: an automatic system for revealing ui-based trigger conditions in android applications. In SPSM’12, pp. 93-104. https://doi.org/10.1145/238193....
 
16.
Zheng, M., Sun, M., & Lui, J. C. (2014). Droidtrace: A ptrace based android dynamic analysis system with forward execution capability. In International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 128–133. https://doi.org/10.1109/IWCMC.....
 
eISSN:1305-8223
ISSN:1305-8215